This proposed project is focused on determining how molecular-level changes in mitochondrial enzymes and transporters that occur in heart disease affect overall cardiac function and determining how therapies may be targeted at the molecular level to improve function at the whole-organ level. The proposed strategy is to first characterize the mitochondrial metabolic network based on quenched kinetic measurements in suspensions of isolated mitochondria. Studies will be carried out using mitochondria obtained from both normal healthy hearts and hearts obtained from a genetic model of hypertension and cardiomyopathy. Large-scale metabolic kinetic measurements will be used to parameterize and validate detailed metabolic models for both the healthy and diseased states. The developed mitochondrial models will be integrated into cell-level models of cardiac energy metabolism, and the cell-level models into a spatially distributed simulation of cardiac oxygen transport that effectively captures spatial gradients and heterogeneity in oxygenation of the myocardium. The resulting tissue-level model will be used for a number of applications: (1) to analyze data on substrate utilization in healthy and diseased states to determine if and how physiological control mechanisms fail in the setting of altered metabolic enzyme activity and expression in the diseased heart. The aim here will be to understand mechanisms leading to reduced capacity to oxidize both fatty acids and carbohydrates, and associated reduction in energetic state, in heart disease; (2) to evaluate metabolic effects of therapeutic strategies tied to metabolic function. We will determine if the model can predict the action of several specific metabolic interventions. The aim here is to develop a powerful platform for an engineering-based approach to under- standing and treating the metabolic effects of heart disease. These analyses may lead to identification of tar- gets or strategies for improving metabolic therapy; and (3) to evaluate if and how regulatory mechanisms respond differently to acute ischemia and recovery in the normal and disease cases. To realize these applications, we must first develop a rigorous simulation platform, integrated from the bottom-up. Specifically, we will start by obtaining kinetic data to identify the organelle-level model from ex vivo experiments (Aim 1). Here we propose to obtain (and make available) time-course kinetic data on 43 metabolic intermediates in response to protocols designed to probe the TCA cycle and 2-oxidation pathways. These data will be used in Aim 2 for model development, parameterization, and validation. Development and application of tissue-level modeling and simulation tools are pursued in Aim 3.